The AR.Drone is a remote controlled quadcopter which is low cost, and readily available for consumers. Therefore it represents a simple test-bed on which control and vision research may be conducted. However, interfacing with the AR.Drone can be a challenge for new researchers as the AR.Drone's application programming interface (API) is built on low-level, bit-wise, C instructions. Therefore, this paper will demonstrate the use of an additional layer of abstraction on the AR.Drone’s API via the Robot Operating System (ROS). Using ROS, the construction of a high-level graphical user interface (GUI) will be demonstrated, with the explicit aim of assisting new researchers in developing simple control and vision algorithms to interface with the AR.Drone. The GUI, formally known as the Control and Vision Interface (CVI) is currently used to research and develop computer vision, simultaneous localisation and mapping (SLAM), and path planning algorithms by a number of postgraduate and undergraduate students at the school of Aeronautical, Mechanical, and Mechatronics Engineering (AMME) in The University of Sydney.
[1]
Daniel Cremers,et al.
Scale-aware navigation of a low-cost quadrocopter with a monocular camera
,
2014,
Robotics Auton. Syst..
[2]
Keiichi Abe,et al.
Topological structural analysis of digitized binary images by border following
,
1985,
Comput. Vis. Graph. Image Process..
[3]
Dirk Eddelbuettel.
A Gentle Introduction to Rcpp
,
2013
.
[4]
G. G. Stokes.
"J."
,
1890,
The New Yale Book of Quotations.
[5]
Hilde Nybom,et al.
Introduction to Rosa
,
2009
.
[6]
Michael Mogenson.
The AR Drone LabVIEW Toolkit: A Software Framework for the Control of Low-Cost Quadrotor Aerial Robots
,
2012
.
[7]
Kyoung-Jae Lee,et al.
MMSE Based Block Diagonalization for Cognitive Radio MIMO Broadcast Channels
,
2011,
IEEE Transactions on Wireless Communications.
[8]
Nicolas Petit,et al.
The Navigation and Control technology inside the AR.Drone micro UAV
,
2011
.